Age-related macular degeneration (AMD) is a progressive retinal disease contributing to blindness worldwide. Multiple estimates for AMD heritability (h2) exist; however, a substantial proportion of h2 is not attributable to known genomic loci. The International AMD Genomics Consortium (IAMDGC) gathered the largest dataset of advanced AMD (ADV) cases and controls available and identified 34 loci containing 52 independent risk variants defining known AMD h2. To better define AMD heterogeneity, we used Pathway Analysis by Randomization Incorporating Structure (PARIS) on the IAMDGC data and identified 8 statistical driver genes (SDGs), including 2 novel SDGs not discovered by the IAMDGC. We chose to further investigate these pathway-based risk genes and determine their contribution to ADV h2, as well as the differential ADV subtype h2. We performed genomic-relatedness-based restricted maximum-likelihood (GREML) analyses on ADV, geographic atrophy (GA), and choroidal neovascularization (CNV) subtypes to investigate the h2 of genotyped variants on the full DNA array chip, 34 risk loci (n = 2758 common variants), 52 variants from the IAMDGC 2016 GWAS, and the 8 SDGs, specifically the novel 2 SDGs, PPARA and PLCG2. Via GREML, full chip h2 was 44.05% for ADV, 46.37% for GA, and 62.03% for CNV. The lead 52 variants’ h2 (ADV: 14.52%, GA: 8.02%, CNV: 13.62%) and 34 loci h2 (ADV: 13.73%, GA: 8.81%, CNV: 12.89%) indicate that known variants contribute ~ 14% to ADV h2. SDG variants account for a small percentage of ADV, GA, and CNV heritability, but estimates based on the combination of SDGs and the 34 known loci are similar to those calculated for known loci alone. We identified modest epistatic interactions among variants in the 2 SDGs and the 52 IAMDGC variants, including modest interactions between variants in PPARA and PLCG2. Pathway analyses, which leverage biological relationships among genes in a pathway, may be useful in identifying additional loci that contribute to the heritability of complex disorders in a non-additive manner. Heritability analyses of these loci, especially amongst disease subtypes, may provide clues to the importance of specific genes to the genetic architecture of AMD.

中文翻译：

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统计驱动基因作为揭示年龄相关性黄斑变性缺失遗传力的一种手段。

年龄相关性黄斑变性（AMD）是一种进行性视网膜疾病，在世界范围内导致失明。存在对AMD遗传力（h2）的多种估计；但是，h2的很大一部分不属于已知的基因组位点。国际AMD基因组学协会（IAMDGC）收集了可用的先进AMD（ADV）病例和对照的最大数据集，并鉴定了34个基因座，其中包含52个定义已知AMD h2的独立风险变体。为了更好地定义AMD异质性，我们在IAMDGC数据上使用了通过随机结合结构（PARIS）进行的路径分析，并鉴定了8个统计驱动基因（SDG），包括2个IAMDGC未发现的新颖SDG。我们选择进一步研究这些基于途径的风险基因，并确定它们对ADV h2以及差异性ADV亚型h2的贡献。我们对ADV，地理萎缩（GA）和脉络膜新血管形成（CNV）亚型进行了基于基因组相关性的有限最大似然（GREML）分析，以研究完整DNA阵列芯片上34个风险位点（n = 2758个常见变体），IAMDGC 2016 GWAS的52个变体和8个SDG，特别是2个SDG，PPARA和PLCG2。通过GREML，ADV的全芯片h2为44.05％，GA为46.37％，CNV为62.03％。前52个变体的h2（ADV：14.52％，GA：8.02％，CNV：13.62％）和34个基因座h2（ADV：13.73％，GA：8.81％，CNV：12.89％）表明已知变体贡献〜14％到ADV h2。SDG变体仅占ADV，GA和CNV遗传力的一小部分，但基于SDG和34个已知基因座的组合进行的估算与仅针对已知基因座的估算值相似。我们确定了2个SDG和52个IAMDGC变体之间的适度上位相互作用，包括PPARA和PLCG2变体之间的适度相互作用。利用通路中基因之间的生物学关系的通路分析可用于识别以非加性方式有助于复杂疾病遗传性的其他基因座。这些基因座的遗传性分析，尤其是在疾病亚型中，可能为特定基因对AMD遗传结构的重要性提供线索。可能有助于确定以非累加方式有助于复杂疾病遗传性的其他基因座。这些基因座的遗传性分析，尤其是在疾病亚型中，可能为特定基因对AMD遗传结构的重要性提供线索。可能有助于确定以非累加方式有助于复杂疾病遗传性的其他基因座。这些基因座的遗传性分析，尤其是在疾病亚型中，可能为特定基因对AMD遗传结构的重要性提供线索。